Multimodal canonical correlation reveals converging neural circuitry across trauma-related disorders of affect and cognition.
Multimodal canonical correlation reveals converging neural circuitry across trauma-related disorders of affect and cognition.
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DOI：
10.1016/j.ynstr.2018.09.006
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发表时间：
2018-11
影响因子：
5
通讯作者：
Simmons AN
中科院分区：
文献类型：
--
作者：
Stout DM;Buchsbaum MS;Spadoni AD;Risbrough VB;Strigo IA;Matthews SC;Simmons AN
创伤相关的情感和认知障碍 (TRAC) 与高度的诊断合并症相关，这可能表明这些疾病具有一组共同的潜在神经机制。 TRAC 的特点是功能和结构回路的异常，有助于语言记忆和情感预期。然而，这些多种机制背后的神经回路如何促成 TRAC 仍然未知。在这里，我们以 47 名退伍军人为样本，使用功能磁共振成像 (fMRI) 测量情感预期，使用氟脱氧葡萄糖正电子发射断层扫描 (FDG-PET) 测量言语记忆，并使用结构磁共振成像 (sMRI) 测量灰质体积。使用基于体素的多模态典型相关分析 (mCCA)，将一组神经测量值与一组 TRAC 症状测量值（包括轻度创伤性脑损伤 (mTBI)、创伤后应激障碍和抑郁严重程度）进行统计整合或融合。第一个典型相关对揭示了包含额中回和补充运动区的神经簇的神经收敛，这些区域涉及自上而下的认知控制和情感调节。这些结果凸显了利用多变量神经影像分析连接与 TRAC 相关的神经生物学机制的潜力，为跨诊断生物标志物和治疗靶点铺平了道路。
Trauma-related disorders of affect and cognition (TRACs) are associated with a high degree of diagnostic comorbidity, which may suggest that these disorders share a set of underlying neural mechanisms. TRACs are characterized by aberrations in functional and structural circuits subserving verbal memory and affective anticipation. Yet, it remains unknown how the neural circuitry underlying these multiple mechanisms contribute to TRACs. Here, in a sample of 47 combat Veterans, we measured affective anticipation using functional magnetic resonance imaging (fMRI), verbal memory with fluorodeoxyglucose positron emission tomography (FDG-PET), and grey matter volume with structural magnetic resonance imaging (sMRI). Using a voxel-based multimodal canonical correlation analysis (mCCA), the set of neural measures were statistically integrated, or fused, with a set of TRAC symptom measures including mild traumatic brain injury (mTBI), posttraumatic stress, and depression severity. The first canonical correlation pair revealed neural convergence in clusters encompassing the middle frontal gyrus and supplemental motor area, regions implicated in top-down cognitive control and affect regulation. These results highlight the potential of leveraging multivariate neuroimaging analysis for linking neurobiological mechanisms associated with TRACs, paving the way for transdiagnostic biomarkers and targets for treatment.
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影响因子：
25.4
作者：
Clark, Lee Anna;Cuthbert, Bruce;Reed, Geoffrey M.
通讯作者：
Reed, Geoffrey M.
影响因子：
6.6
作者：
Bomyea, J.;Matthews, S. C.;Simmons, A. N.
通讯作者：
Simmons, A. N.
影响因子：
2.9
作者：
Dean PJ;Sterr A
通讯作者：
Sterr A
影响因子：
4.7
作者：
Acheson DT;Gresack JE;Risbrough VB
通讯作者：
Risbrough VB
影响因子：
5.7
作者：
Avants BB;Tustison NJ;Song G;Cook PA;Klein A;Gee JC
通讯作者：
Gee JC